| name | review |
| description | Review, either de-novo, or augment the review of an existing one. A list of deep research providers may be specified. |
| argument-hint | [ORGANISM] [GENE_SYMBOL] (using [DEEP_RESEARCH_PROVIDER]) |
Review the gene specified in $ARGUMENTS.
- ORGANISM should typically be a uniprot species code (in a few cases we use lowercase GO names)
- GENE_SYMBOL should be the human readable gene symbol for that org
IMPORTANT: you MUST consult the annotation-reviewer.md subagent for this task.
Step 1: Ensure gene data is fetched
Run just fetch-gene ORGANISM GENE_SYMBOL if the gene directory doesn't exist yet.
Step 2: Run deep research AND publication caching in parallel
Publication caching only needs the GOA file (created by fetch-gene), so it can run
concurrently with deep research. Launch both at the same time:
- Deep research: If the user specifies a deep research provider(s), use that provider(s),
otherwise default to falcon. Use
--fallback perplexity-lite so that if the primary
provider times out, it automatically retries with perplexity-lite.
E.g. just deep-research-falcon ORGANISM GENE_SYMBOL --fallback perplexity-lite
- Publication caching:
just fetch-gene-pmids ORGANISM GENE_SYMBOL
Run these two steps in parallel (e.g. as concurrent background agents or shell jobs).
Do NOT wait for deep research to finish before starting publication caching.
Step 3: Fetch additional data (bacterial organisms)
For bacterial organisms (e.g. PSEPK, ECOLI, SALTY, or any prokaryote), after deep research,
also fetch FEBA/RB-TnSeq fitness data if available:
just fetch-fitness ORGANISM GENE_SYMBOL
This creates a GENE-fitness.md file with mutant fitness phenotypes and cofitness partners.
The annotation-reviewer agent will use this data as additional evidence when reviewing annotations.
Step 4: Run annotation review
Invoke the annotation-reviewer subagent to systematically review all annotations.
